TY - JOUR AU - O’kane, Philip AU - Sezer, Sakir AU - McLaughlin, Kieran PY - 2016 DA - 2016/05/04 TI - Detecting obfuscated malware using reduced opcode set and optimised runtime trace JO - Security Informatics SP - 2 VL - 5 IS - 1 AB - The research presented, investigates the optimal set of operational codes (opcodes) that create a robust indicator of malicious software (malware) and also determines a program’s execution duration for accurate classification of benign and malicious software. The features extracted from the dataset are opcode density histograms, extracted during the program execution. The classifier used is a support vector machine and is configured to select those features to produce the optimal classification of malware over different program run lengths. The findings demonstrate that malware can be detected using dynamic analysis with relatively few opcodes. SN - 2190-8532 UR - https://doi.org/10.1186/s13388-016-0027-2 DO - 10.1186/s13388-016-0027-2 ID - O’kane2016 ER -